scholarly journals Raman profile alterations of irradiated human nasopharyngeal cancer cells detected with laser tweezer Raman spectroscopy

RSC Advances ◽  
2020 ◽  
Vol 10 (24) ◽  
pp. 14368-14373 ◽  
Author(s):  
Sufang Qiu ◽  
Youliang Weng ◽  
Ying Li ◽  
Yang Chen ◽  
Yuhui Pan ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Statistical Analysis ◽  
Tumor Cell ◽  
Cancer Cells ◽  
Multivariate Statistical Analysis ◽  
Nasopharyngeal Cancer ◽  
Multivariate Statistical ◽  
Laser Tweezer ◽  
Single Tumor Cell ◽  
Single Tumor

Laser tweezer Raman spectroscopy combined with multivariate statistical analysis was used for evaluating the radiotherapeutic effect on a single tumor cell.

scholarly journals Label-Free Exosomal Detection and Classification in Rapid Discriminating Different Cancer Types Based on Specific Raman Phenotypes and Multivariate Statistical Analysis

Molecules ◽  
2019 ◽  
Vol 24 (16) ◽  
pp. 2947 ◽  
Author(s):  
Ping Zhang ◽  
Limin Wang ◽  
Yaping Fang ◽  
Dawei Zheng ◽  
Taifeng Lin ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Cancer Cells ◽  
Multivariate Statistical Analysis ◽  
Cell Types ◽  
Rapid Screening ◽  
Label Free ◽  
Multivariate Statistical ◽  
Normal Cells ◽  
Cancer Types ◽  
New Biomarkers

Exosomes contain different functional bimolecular characteristics related to physiological or pathological processes and are now recognized as new biomarkers in different human cancers. Rapid detection and classification of cancer-related exosomes might be helpful in the rapid screening of patients that may have cancer. Here, we report a surface enhanced Raman scattering technology for rapid and label-free exosomal detection (Exo-SERS) to aid in the discrimination of different cancer cells based on specific Raman phenotypes and multivariate statistical analysis. The results demonstrated that exosomes derived from both tumor cells and normal cells exhibit special, unique Raman phenotypes. Using the Exo-SERS method, the cancer cells were accurately discriminated from normal cells, and subtle molecular changes between the different cell types could be detected with high sensitive. This research provides a rapid, label-free and non-destructive manner for detecting and discriminating between cancer types.

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